March 2, 2021
Clickhouse is an open-source columnar-oriented Database Management System (DBMS) used for online analytical processing (OLAP) created by Yandex. Currently, it powers the second largest web analytics platform, Yandex Metrica. It can also be considered the first open-source SQL data warehouse to ever match the scalability and performance of databases such as Veryica and Snowflake.

Released in open source in 2016, ClickHouse is used by Yandex for the purposes of KPIs and site accessibility monitoring. It has also been implemented at CERN’s LHCb experiment where it stores and processes metadata on 10 billion events housing over 1000 attributes in one event.

Clickhouse is mainly used by analysts/DevOps engineers/Developers, Startups looking for high-quality analytics with low capital, and companies paying hefty amounts of money for architecture.

How Clickhouse Operates

Unlike most proprietary databases, Clickhouse development is driven by a committed community made up of hundreds of contributors focused on creating better functionality and solving problems that may degrade its performance.

By using all available hardware to process each query, the application can process a whopping 100 million to more than a billion rows and gigs of data per one-second server cycle.

Clickhouse allows companies and developers to add servers to their clusters without pumping in a lot of resources into DBMS modification.

Clickhouse Features

Here are some of the main features of ClickHouse DBMS:

  • Offers linear scalability
  • Storage and processing of petabytes of data
  • Data compression
  • HDD optimization
  • Fault tolerance
  • High performance such as distributed and parallel query processing
  • Support for SQL

Advantages of ClickHouse

  • Distributed processing on several servers
  • Easy to set up and has good documentation and community
  • ClickHouse is Effective when working with denormalized/wide tables
  • Index support
  • Fast scans that can be utilized for real-time queries
  • Utilization of multiple cores in parallel processing for single queries
  • User-friendly command line
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